Overview

Brought to you by YData

Dataset statistics

Number of variables12
Number of observations2969
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory301.5 KiB
Average record size in memory104.0 B

Variable types

Numeric12

Alerts

avg_basket_size is highly overall correlated with gross_revenue and 1 other fieldsHigh correlation
avg_recency_days is highly overall correlated with frequencyHigh correlation
avg_ticket is highly overall correlated with avg_unique_basket_sizeHigh correlation
avg_unique_basket_size is highly overall correlated with avg_ticket and 1 other fieldsHigh correlation
frequency is highly overall correlated with avg_recency_daysHigh correlation
gross_revenue is highly overall correlated with avg_basket_size and 3 other fieldsHigh correlation
qtd_invoices is highly overall correlated with gross_revenue and 3 other fieldsHigh correlation
qtd_items is highly overall correlated with avg_basket_size and 3 other fieldsHigh correlation
qtd_products is highly overall correlated with avg_unique_basket_size and 3 other fieldsHigh correlation
recency_days is highly overall correlated with qtd_invoicesHigh correlation
avg_ticket is highly skewed (γ1 = 53.44422359) Skewed
qtd_returns is highly skewed (γ1 = 51.79774426) Skewed
avg_basket_size is highly skewed (γ1 = 44.67271661) Skewed
customer_id has unique values Unique
recency_days has 34 (1.1%) zeros Zeros
qtd_returns has 1481 (49.9%) zeros Zeros

Reproduction

Analysis started2025-03-08 00:23:06.430456
Analysis finished2025-03-08 00:23:35.916715
Duration29.49 seconds
Software versionydata-profiling vv4.13.0
Download configurationconfig.json

Variables

customer_id
Real number (ℝ)

Unique 

Distinct2969
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean15270.773
Minimum12347
Maximum18287
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size46.4 KiB
2025-03-07T21:23:36.044638image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/

Quantile statistics

Minimum12347
5-th percentile12619.4
Q113799
median15221
Q316768
95-th percentile17964.6
Maximum18287
Range5940
Interquartile range (IQR)2969

Descriptive statistics

Standard deviation1718.9903
Coefficient of variation (CV)0.11256734
Kurtosis-1.2060947
Mean15270.773
Median Absolute Deviation (MAD)1488
Skewness0.031607859
Sum45338925
Variance2954927.6
MonotonicityNot monotonic
2025-03-07T21:23:36.260601image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
12558 1
 
< 0.1%
17850 1
 
< 0.1%
13047 1
 
< 0.1%
12583 1
 
< 0.1%
13748 1
 
< 0.1%
15100 1
 
< 0.1%
15291 1
 
< 0.1%
14688 1
 
< 0.1%
17809 1
 
< 0.1%
16956 1
 
< 0.1%
Other values (2959) 2959
99.7%
ValueCountFrequency (%)
12347 1
< 0.1%
12348 1
< 0.1%
12352 1
< 0.1%
12356 1
< 0.1%
12358 1
< 0.1%
12359 1
< 0.1%
12360 1
< 0.1%
12362 1
< 0.1%
12364 1
< 0.1%
12370 1
< 0.1%
ValueCountFrequency (%)
18287 1
< 0.1%
18283 1
< 0.1%
18282 1
< 0.1%
18277 1
< 0.1%
18276 1
< 0.1%
18274 1
< 0.1%
18273 1
< 0.1%
18272 1
< 0.1%
18270 1
< 0.1%
18269 1
< 0.1%

gross_revenue
Real number (ℝ)

High correlation 

Distinct2954
Distinct (%)99.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2749.3217
Minimum6.2
Maximum279138.02
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size46.4 KiB
2025-03-07T21:23:36.459646image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/

Quantile statistics

Minimum6.2
5-th percentile229.77
Q1570.96
median1086.92
Q32308.06
95-th percentile7219.68
Maximum279138.02
Range279131.82
Interquartile range (IQR)1737.1

Descriptive statistics

Standard deviation10580.623
Coefficient of variation (CV)3.8484486
Kurtosis353.94472
Mean2749.3217
Median Absolute Deviation (MAD)672.16
Skewness16.777556
Sum8162736.2
Variance1.1194959 × 108
MonotonicityNot monotonic
2025-03-07T21:23:36.668702image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
533.33 2
 
0.1%
734.94 2
 
0.1%
178.96 2
 
0.1%
1078.96 2
 
0.1%
598.2 2
 
0.1%
1314.45 2
 
0.1%
379.65 2
 
0.1%
2053.02 2
 
0.1%
331 2
 
0.1%
889.93 2
 
0.1%
Other values (2944) 2949
99.3%
ValueCountFrequency (%)
6.2 1
< 0.1%
13.3 1
< 0.1%
15 1
< 0.1%
36.56 1
< 0.1%
45 1
< 0.1%
52 1
< 0.1%
52.2 1
< 0.1%
52.2 1
< 0.1%
62.43 1
< 0.1%
68.84 1
< 0.1%
ValueCountFrequency (%)
279138.02 1
< 0.1%
259657.3 1
< 0.1%
194550.79 1
< 0.1%
168472.5 1
< 0.1%
140450.72 1
< 0.1%
124564.53 1
< 0.1%
117379.63 1
< 0.1%
91062.38 1
< 0.1%
72882.09 1
< 0.1%
66653.56 1
< 0.1%

recency_days
Real number (ℝ)

High correlation  Zeros 

Distinct272
Distinct (%)9.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean64.287639
Minimum0
Maximum373
Zeros34
Zeros (%)1.1%
Negative0
Negative (%)0.0%
Memory size46.4 KiB
2025-03-07T21:23:36.872743image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2
Q111
median31
Q381
95-th percentile242
Maximum373
Range373
Interquartile range (IQR)70

Descriptive statistics

Standard deviation77.756779
Coefficient of variation (CV)1.2095137
Kurtosis2.7779627
Mean64.287639
Median Absolute Deviation (MAD)26
Skewness1.7983795
Sum190870
Variance6046.1167
MonotonicityNot monotonic
2025-03-07T21:23:37.166807image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 99
 
3.3%
4 87
 
2.9%
3 85
 
2.9%
2 85
 
2.9%
8 76
 
2.6%
10 67
 
2.3%
9 66
 
2.2%
7 66
 
2.2%
17 64
 
2.2%
16 55
 
1.9%
Other values (262) 2219
74.7%
ValueCountFrequency (%)
0 34
 
1.1%
1 99
3.3%
2 85
2.9%
3 85
2.9%
4 87
2.9%
5 43
1.4%
7 66
2.2%
8 76
2.6%
9 66
2.2%
10 67
2.3%
ValueCountFrequency (%)
373 2
0.1%
372 4
0.1%
371 1
 
< 0.1%
368 1
 
< 0.1%
366 4
0.1%
365 2
0.1%
364 1
 
< 0.1%
360 1
 
< 0.1%
359 1
 
< 0.1%
358 4
0.1%

qtd_invoices
Real number (ℝ)

High correlation 

Distinct56
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.7231391
Minimum1
Maximum206
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size46.4 KiB
2025-03-07T21:23:37.430168image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median4
Q36
95-th percentile17
Maximum206
Range205
Interquartile range (IQR)4

Descriptive statistics

Standard deviation8.8565313
Coefficient of variation (CV)1.5474954
Kurtosis190.83445
Mean5.7231391
Median Absolute Deviation (MAD)2
Skewness10.766805
Sum16992
Variance78.438147
MonotonicityNot monotonic
2025-03-07T21:23:38.045269image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2 785
26.4%
3 499
16.8%
4 393
13.2%
5 237
 
8.0%
1 190
 
6.4%
6 173
 
5.8%
7 138
 
4.6%
8 98
 
3.3%
9 69
 
2.3%
10 55
 
1.9%
Other values (46) 332
11.2%
ValueCountFrequency (%)
1 190
 
6.4%
2 785
26.4%
3 499
16.8%
4 393
13.2%
5 237
 
8.0%
6 173
 
5.8%
7 138
 
4.6%
8 98
 
3.3%
9 69
 
2.3%
10 55
 
1.9%
ValueCountFrequency (%)
206 1
< 0.1%
199 1
< 0.1%
124 1
< 0.1%
97 1
< 0.1%
91 2
0.1%
86 1
< 0.1%
72 1
< 0.1%
62 2
0.1%
60 1
< 0.1%
57 1
< 0.1%

qtd_items
Real number (ℝ)

High correlation 

Distinct1671
Distinct (%)56.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1608.8525
Minimum1
Maximum196844
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size46.4 KiB
2025-03-07T21:23:38.244368image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile102.4
Q1296
median641
Q31401
95-th percentile4407.4
Maximum196844
Range196843
Interquartile range (IQR)1105

Descriptive statistics

Standard deviation5887.578
Coefficient of variation (CV)3.6594891
Kurtosis465.99808
Mean1608.8525
Median Absolute Deviation (MAD)422
Skewness17.858591
Sum4776683
Variance34663575
MonotonicityNot monotonic
2025-03-07T21:23:38.463259image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
310 11
 
0.4%
150 9
 
0.3%
88 9
 
0.3%
84 8
 
0.3%
260 8
 
0.3%
288 8
 
0.3%
272 8
 
0.3%
246 8
 
0.3%
114 7
 
0.2%
134 7
 
0.2%
Other values (1661) 2886
97.2%
ValueCountFrequency (%)
1 1
< 0.1%
2 2
0.1%
12 2
0.1%
16 1
< 0.1%
17 1
< 0.1%
18 1
< 0.1%
19 1
< 0.1%
20 1
< 0.1%
23 1
< 0.1%
25 1
< 0.1%
ValueCountFrequency (%)
196844 1
< 0.1%
80997 1
< 0.1%
80263 1
< 0.1%
77373 1
< 0.1%
69993 1
< 0.1%
64549 1
< 0.1%
64124 1
< 0.1%
63312 1
< 0.1%
58343 1
< 0.1%
57885 1
< 0.1%

qtd_products
Real number (ℝ)

High correlation 

Distinct468
Distinct (%)15.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean122.72415
Minimum1
Maximum7838
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size46.4 KiB
2025-03-07T21:23:38.683359image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile9
Q129
median67
Q3135
95-th percentile382
Maximum7838
Range7837
Interquartile range (IQR)106

Descriptive statistics

Standard deviation269.89641
Coefficient of variation (CV)2.1992119
Kurtosis354.86113
Mean122.72415
Median Absolute Deviation (MAD)44
Skewness15.707635
Sum364368
Variance72844.071
MonotonicityNot monotonic
2025-03-07T21:23:38.896815image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
28 43
 
1.4%
20 37
 
1.2%
29 35
 
1.2%
35 35
 
1.2%
19 34
 
1.1%
15 33
 
1.1%
11 32
 
1.1%
26 31
 
1.0%
27 30
 
1.0%
25 30
 
1.0%
Other values (458) 2629
88.5%
ValueCountFrequency (%)
1 6
 
0.2%
2 14
0.5%
3 16
0.5%
4 17
0.6%
5 26
0.9%
6 29
1.0%
7 18
0.6%
8 19
0.6%
9 26
0.9%
10 28
0.9%
ValueCountFrequency (%)
7838 1
< 0.1%
5673 1
< 0.1%
5095 1
< 0.1%
4580 1
< 0.1%
2698 1
< 0.1%
2379 1
< 0.1%
2060 1
< 0.1%
1818 1
< 0.1%
1673 1
< 0.1%
1637 1
< 0.1%

avg_ticket
Real number (ℝ)

High correlation  Skewed 

Distinct2000
Distinct (%)67.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean51.897713
Minimum2.15
Maximum56157.5
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size46.4 KiB
2025-03-07T21:23:39.098841image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/

Quantile statistics

Minimum2.15
5-th percentile4.918
Q113.12
median17.96
Q324.99
95-th percentile90.498
Maximum56157.5
Range56155.35
Interquartile range (IQR)11.87

Descriptive statistics

Standard deviation1036.9344
Coefficient of variation (CV)19.980349
Kurtosis2890.7071
Mean51.897713
Median Absolute Deviation (MAD)5.98
Skewness53.444224
Sum154084.31
Variance1075233
MonotonicityNot monotonic
2025-03-07T21:23:39.303823image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
15.49 7
 
0.2%
17.66 6
 
0.2%
16.39 6
 
0.2%
16.82 6
 
0.2%
16.92 6
 
0.2%
19.06 6
 
0.2%
20.75 5
 
0.2%
10 5
 
0.2%
18.38 5
 
0.2%
17.71 5
 
0.2%
Other values (1990) 2912
98.1%
ValueCountFrequency (%)
2.15 1
< 0.1%
2.43 1
< 0.1%
2.46 1
< 0.1%
2.51 1
< 0.1%
2.52 1
< 0.1%
2.65 1
< 0.1%
2.66 1
< 0.1%
2.71 1
< 0.1%
2.76 1
< 0.1%
2.77 1
< 0.1%
ValueCountFrequency (%)
56157.5 1
< 0.1%
4453.43 1
< 0.1%
3202.92 1
< 0.1%
1687.2 1
< 0.1%
952.99 1
< 0.1%
872.13 1
< 0.1%
841.02 1
< 0.1%
651.17 1
< 0.1%
640 1
< 0.1%
624.4 1
< 0.1%

avg_recency_days
Real number (ℝ)

High correlation 

Distinct1258
Distinct (%)42.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-67.348511
Minimum-366
Maximum-1
Zeros0
Zeros (%)0.0%
Negative2969
Negative (%)100.0%
Memory size46.4 KiB
2025-03-07T21:23:39.504827image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/

Quantile statistics

Minimum-366
5-th percentile-201
Q1-85.333333
median-48.285714
Q3-25.923077
95-th percentile-8
Maximum-1
Range365
Interquartile range (IQR)59.410256

Descriptive statistics

Standard deviation63.544929
Coefficient of variation (CV)-0.94352388
Kurtosis4.8871091
Mean-67.348511
Median Absolute Deviation (MAD)26.285714
Skewness-2.0627709
Sum-199957.73
Variance4037.958
MonotonicityNot monotonic
2025-03-07T21:23:39.725855image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-14 25
 
0.8%
-4 22
 
0.7%
-70 21
 
0.7%
-7 20
 
0.7%
-35 19
 
0.6%
-49 18
 
0.6%
-21 17
 
0.6%
-46 17
 
0.6%
-11 17
 
0.6%
-42 16
 
0.5%
Other values (1248) 2777
93.5%
ValueCountFrequency (%)
-366 1
 
< 0.1%
-365 1
 
< 0.1%
-363 1
 
< 0.1%
-362 1
 
< 0.1%
-357 2
0.1%
-356 1
 
< 0.1%
-355 2
0.1%
-352 1
 
< 0.1%
-351 2
0.1%
-350 3
0.1%
ValueCountFrequency (%)
-1 16
0.5%
-1.5 1
 
< 0.1%
-2 13
0.4%
-2.5 1
 
< 0.1%
-2.601398601 1
 
< 0.1%
-3 15
0.5%
-3.321428571 1
 
< 0.1%
-3.330357143 1
 
< 0.1%
-3.5 2
 
0.1%
-4 22
0.7%

frequency
Real number (ℝ)

High correlation 

Distinct1350
Distinct (%)45.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.063278078
Minimum0.0054495913
Maximum3
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size46.4 KiB
2025-03-07T21:23:39.936858image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/

Quantile statistics

Minimum0.0054495913
5-th percentile0.0094339623
Q10.017777778
median0.029411765
Q30.055401662
95-th percentile0.22222222
Maximum3
Range2.9945504
Interquartile range (IQR)0.037623884

Descriptive statistics

Standard deviation0.13448206
Coefficient of variation (CV)2.1252552
Kurtosis121.55755
Mean0.063278078
Median Absolute Deviation (MAD)0.014338235
Skewness8.7732594
Sum187.87261
Variance0.018085426
MonotonicityNot monotonic
2025-03-07T21:23:40.157850image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.3333333333 21
 
0.7%
0.1666666667 21
 
0.7%
0.02777777778 20
 
0.7%
0.09090909091 19
 
0.6%
0.0625 17
 
0.6%
0.1333333333 16
 
0.5%
0.4 16
 
0.5%
0.02380952381 15
 
0.5%
0.25 15
 
0.5%
0.03571428571 15
 
0.5%
Other values (1340) 2794
94.1%
ValueCountFrequency (%)
0.005449591281 1
 
< 0.1%
0.005464480874 1
 
< 0.1%
0.005494505495 1
 
< 0.1%
0.005509641873 1
 
< 0.1%
0.005586592179 2
0.1%
0.005602240896 1
 
< 0.1%
0.005617977528 2
0.1%
0.00566572238 1
 
< 0.1%
0.005681818182 2
0.1%
0.005698005698 3
0.1%
ValueCountFrequency (%)
3 1
 
< 0.1%
2 1
 
< 0.1%
1.571428571 1
 
< 0.1%
1.5 3
 
0.1%
1 14
0.5%
0.8333333333 1
 
< 0.1%
0.75 1
 
< 0.1%
0.6666666667 12
0.4%
0.6514745308 1
 
< 0.1%
0.6 1
 
< 0.1%

qtd_returns
Real number (ℝ)

Skewed  Zeros 

Distinct214
Distinct (%)7.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean62.156955
Minimum0
Maximum80995
Zeros1481
Zeros (%)49.9%
Negative0
Negative (%)0.0%
Memory size46.4 KiB
2025-03-07T21:23:40.374838image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q39
95-th percentile100.6
Maximum80995
Range80995
Interquartile range (IQR)9

Descriptive statistics

Standard deviation1512.4961
Coefficient of variation (CV)24.333498
Kurtosis2765.5286
Mean62.156955
Median Absolute Deviation (MAD)1
Skewness51.797744
Sum184544
Variance2287644.6
MonotonicityNot monotonic
2025-03-07T21:23:40.599840image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 1481
49.9%
1 164
 
5.5%
2 148
 
5.0%
3 105
 
3.5%
4 89
 
3.0%
6 78
 
2.6%
5 61
 
2.1%
12 51
 
1.7%
8 43
 
1.4%
7 43
 
1.4%
Other values (204) 706
23.8%
ValueCountFrequency (%)
0 1481
49.9%
1 164
 
5.5%
2 148
 
5.0%
3 105
 
3.5%
4 89
 
3.0%
5 61
 
2.1%
6 78
 
2.6%
7 43
 
1.4%
8 43
 
1.4%
9 41
 
1.4%
ValueCountFrequency (%)
80995 1
< 0.1%
9014 1
< 0.1%
8004 1
< 0.1%
4427 1
< 0.1%
3768 1
< 0.1%
3332 1
< 0.1%
2878 1
< 0.1%
2022 1
< 0.1%
2012 1
< 0.1%
1776 1
< 0.1%

avg_basket_size
Real number (ℝ)

High correlation  Skewed 

Distinct1979
Distinct (%)66.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean249.81376
Minimum1
Maximum40498.5
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size46.4 KiB
2025-03-07T21:23:40.825846image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile44
Q1103.25
median172.33333
Q3281.69231
95-th percentile600
Maximum40498.5
Range40497.5
Interquartile range (IQR)178.44231

Descriptive statistics

Standard deviation791.55519
Coefficient of variation (CV)3.1685812
Kurtosis2255.5382
Mean249.81376
Median Absolute Deviation (MAD)83.083333
Skewness44.672717
Sum741697.07
Variance626559.62
MonotonicityNot monotonic
2025-03-07T21:23:41.051864image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
100 11
 
0.4%
114 10
 
0.3%
73 9
 
0.3%
86 9
 
0.3%
82 9
 
0.3%
136 8
 
0.3%
75 8
 
0.3%
88 8
 
0.3%
60 8
 
0.3%
130 7
 
0.2%
Other values (1969) 2882
97.1%
ValueCountFrequency (%)
1 2
0.1%
2 1
< 0.1%
3.333333333 1
< 0.1%
5.333333333 1
< 0.1%
5.666666667 1
< 0.1%
6.142857143 1
< 0.1%
7.5 1
< 0.1%
9 1
< 0.1%
9.5 1
< 0.1%
11 1
< 0.1%
ValueCountFrequency (%)
40498.5 1
< 0.1%
6009.333333 1
< 0.1%
4282 1
< 0.1%
3906 1
< 0.1%
3868.65 1
< 0.1%
2880 1
< 0.1%
2801 1
< 0.1%
2733.944444 1
< 0.1%
2518.769231 1
< 0.1%
2160.333333 1
< 0.1%

avg_unique_basket_size
Real number (ℝ)

High correlation 

Distinct1005
Distinct (%)33.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean22.154708
Minimum1
Maximum299.70588
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size46.4 KiB
2025-03-07T21:23:41.278843image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3.3454545
Q110
median17.2
Q327.75
95-th percentile56.94
Maximum299.70588
Range298.70588
Interquartile range (IQR)17.75

Descriptive statistics

Standard deviation19.512322
Coefficient of variation (CV)0.88073027
Kurtosis27.703297
Mean22.154708
Median Absolute Deviation (MAD)8.2
Skewness3.4994559
Sum65777.329
Variance380.73071
MonotonicityNot monotonic
2025-03-07T21:23:41.638843image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
13 53
 
1.8%
14 39
 
1.3%
11 38
 
1.3%
9 33
 
1.1%
20 33
 
1.1%
1 32
 
1.1%
17 31
 
1.0%
18 30
 
1.0%
10 30
 
1.0%
16 29
 
1.0%
Other values (995) 2621
88.3%
ValueCountFrequency (%)
1 32
1.1%
1.2 1
 
< 0.1%
1.25 1
 
< 0.1%
1.333333333 2
 
0.1%
1.5 8
 
0.3%
1.568181818 1
 
< 0.1%
1.571428571 1
 
< 0.1%
1.666666667 4
 
0.1%
1.833333333 1
 
< 0.1%
2 24
0.8%
ValueCountFrequency (%)
299.7058824 1
< 0.1%
259 1
< 0.1%
203.5 1
< 0.1%
148 1
< 0.1%
145 1
< 0.1%
136.125 1
< 0.1%
135.5 1
< 0.1%
127 1
< 0.1%
122 1
< 0.1%
118 1
< 0.1%

Interactions

2025-03-07T21:23:33.335700image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
2025-03-07T21:23:06.804543image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
2025-03-07T21:23:09.071439image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
2025-03-07T21:23:11.225779image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
2025-03-07T21:23:13.862376image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
2025-03-07T21:23:16.263993image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
2025-03-07T21:23:19.606477image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
2025-03-07T21:23:21.833983image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
2025-03-07T21:23:23.799427image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
2025-03-07T21:23:25.977919image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
2025-03-07T21:23:28.382465image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
2025-03-07T21:23:30.684099image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
2025-03-07T21:23:33.510739image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
2025-03-07T21:23:06.979580image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
2025-03-07T21:23:09.243478image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
2025-03-07T21:23:11.401827image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
2025-03-07T21:23:14.037416image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
2025-03-07T21:23:16.492392image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
2025-03-07T21:23:19.809524image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
2025-03-07T21:23:21.994017image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
2025-03-07T21:23:23.980467image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
2025-03-07T21:23:26.154961image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
2025-03-07T21:23:28.562505image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
2025-03-07T21:23:30.871147image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
2025-03-07T21:23:33.738792image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
2025-03-07T21:23:07.170624image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
2025-03-07T21:23:09.424518image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
2025-03-07T21:23:11.635872image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
2025-03-07T21:23:14.213455image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
2025-03-07T21:23:16.694437image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
2025-03-07T21:23:19.994566image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
2025-03-07T21:23:22.158057image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
2025-03-07T21:23:24.151507image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
2025-03-07T21:23:26.322999image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
2025-03-07T21:23:28.740546image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
2025-03-07T21:23:31.055185image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
2025-03-07T21:23:33.935837image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
2025-03-07T21:23:07.355667image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
2025-03-07T21:23:09.655572image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
2025-03-07T21:23:11.873926image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
2025-03-07T21:23:14.394496image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
2025-03-07T21:23:16.922491image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
2025-03-07T21:23:20.184609image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
2025-03-07T21:23:22.324102image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
2025-03-07T21:23:24.328549image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
2025-03-07T21:23:26.494037image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
2025-03-07T21:23:28.919586image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
2025-03-07T21:23:31.246229image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
2025-03-07T21:23:34.090746image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
2025-03-07T21:23:07.516839image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
2025-03-07T21:23:09.822611image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
2025-03-07T21:23:12.076971image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
2025-03-07T21:23:14.559534image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
2025-03-07T21:23:17.105532image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
2025-03-07T21:23:20.352650image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
2025-03-07T21:23:22.476131image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
2025-03-07T21:23:24.495584image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
2025-03-07T21:23:26.652073image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
2025-03-07T21:23:29.085955image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
2025-03-07T21:23:31.424267image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
2025-03-07T21:23:34.272788image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
2025-03-07T21:23:07.706987image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
2025-03-07T21:23:10.005670image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
2025-03-07T21:23:12.317026image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
2025-03-07T21:23:14.772584image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
2025-03-07T21:23:17.301504image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
2025-03-07T21:23:20.544690image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
2025-03-07T21:23:22.655167image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
2025-03-07T21:23:24.681627image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
2025-03-07T21:23:26.837115image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
2025-03-07T21:23:29.267398image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
2025-03-07T21:23:31.623313image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
2025-03-07T21:23:34.446825image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
2025-03-07T21:23:07.891031image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
2025-03-07T21:23:10.184735image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
2025-03-07T21:23:12.587088image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
2025-03-07T21:23:14.973626image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
2025-03-07T21:23:17.494522image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
2025-03-07T21:23:20.724729image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
2025-03-07T21:23:22.829208image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
2025-03-07T21:23:24.860667image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
2025-03-07T21:23:27.012155image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
2025-03-07T21:23:29.456451image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
2025-03-07T21:23:31.830360image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
2025-03-07T21:23:34.613864image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
2025-03-07T21:23:08.052067image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
2025-03-07T21:23:10.348089image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
2025-03-07T21:23:12.830142image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
2025-03-07T21:23:15.161673image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
2025-03-07T21:23:17.684562image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
2025-03-07T21:23:20.909774image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
2025-03-07T21:23:22.976241image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
2025-03-07T21:23:25.023704image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
2025-03-07T21:23:27.177192image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
2025-03-07T21:23:29.632862image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
2025-03-07T21:23:32.157434image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
2025-03-07T21:23:34.782906image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
2025-03-07T21:23:08.233249image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
2025-03-07T21:23:10.531622image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
2025-03-07T21:23:13.046193image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
2025-03-07T21:23:15.369716image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
2025-03-07T21:23:17.872725image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
2025-03-07T21:23:21.099814image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
2025-03-07T21:23:23.137277image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
2025-03-07T21:23:25.194743image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
2025-03-07T21:23:27.694308image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
2025-03-07T21:23:29.881918image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
2025-03-07T21:23:32.397488image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
2025-03-07T21:23:34.948769image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
2025-03-07T21:23:08.396284image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
2025-03-07T21:23:10.695658image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
2025-03-07T21:23:13.244236image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
2025-03-07T21:23:15.563760image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
2025-03-07T21:23:18.071968image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
2025-03-07T21:23:21.277857image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
2025-03-07T21:23:23.297311image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
2025-03-07T21:23:25.439797image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
2025-03-07T21:23:27.861348image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
2025-03-07T21:23:30.104968image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
2025-03-07T21:23:32.653548image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
2025-03-07T21:23:35.127809image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
2025-03-07T21:23:08.590332image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
2025-03-07T21:23:10.877702image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
2025-03-07T21:23:13.461285image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
2025-03-07T21:23:15.867832image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
2025-03-07T21:23:18.290179image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
2025-03-07T21:23:21.465898image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
2025-03-07T21:23:23.463353image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
2025-03-07T21:23:25.625841image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
2025-03-07T21:23:28.041388image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
2025-03-07T21:23:30.299012image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
2025-03-07T21:23:32.861596image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
2025-03-07T21:23:35.316919image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
2025-03-07T21:23:08.845390image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
2025-03-07T21:23:11.057750image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
2025-03-07T21:23:13.673333image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
2025-03-07T21:23:16.083953image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
2025-03-07T21:23:19.402429image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
2025-03-07T21:23:21.653943image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
2025-03-07T21:23:23.632389image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
2025-03-07T21:23:25.808882image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
2025-03-07T21:23:28.220428image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
2025-03-07T21:23:30.499059image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
2025-03-07T21:23:33.095646image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/

Correlations

2025-03-07T21:23:41.871848image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
avg_basket_sizeavg_recency_daysavg_ticketavg_unique_basket_sizecustomer_idfrequencygross_revenueqtd_invoicesqtd_itemsqtd_productsqtd_returnsrecency_days
avg_basket_size1.0000.0770.1880.447-0.1230.0570.5740.1000.7290.3830.210-0.098
avg_recency_days0.0771.0000.122-0.048-0.0190.9620.2470.2590.2270.1660.396-0.108
avg_ticket0.1880.1221.000-0.611-0.1310.0980.2460.0590.167-0.3770.1900.048
avg_unique_basket_size0.447-0.048-0.6111.000-0.007-0.0420.2910.0250.3200.6990.019-0.106
customer_id-0.123-0.019-0.131-0.0071.000-0.008-0.0760.026-0.0700.013-0.0630.001
frequency0.0570.9620.098-0.042-0.0081.0000.1610.1490.1450.1010.359-0.031
gross_revenue0.5740.2470.2460.291-0.0760.1611.0000.7700.9250.7440.372-0.415
qtd_invoices0.1000.2590.0590.0250.0260.1490.7701.0000.7160.6900.294-0.502
qtd_items0.7290.2270.1670.320-0.0700.1450.9250.7161.0000.7300.344-0.408
qtd_products0.3830.166-0.3770.6990.0130.1010.7440.6900.7301.0000.242-0.435
qtd_returns0.2100.3960.1900.019-0.0630.3590.3720.2940.3440.2421.000-0.120
recency_days-0.098-0.1080.048-0.1060.001-0.031-0.415-0.502-0.408-0.435-0.1201.000

Missing values

2025-03-07T21:23:35.573196image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
A simple visualization of nullity by column.
2025-03-07T21:23:35.790685image/svg+xmlMatplotlib v3.10.1, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

customer_idgross_revenuerecency_daysqtd_invoicesqtd_itemsqtd_productsavg_ticketavg_recency_daysfrequencyqtd_returnsavg_basket_sizeavg_unique_basket_size
0178505391.21372.034.01733.0297.018.15-35.5000000.48611140.050.9705888.735294
1130473232.5956.09.01390.0171.018.90-27.2500000.04878035.0154.44444419.000000
2125836705.382.015.05028.0232.028.90-23.1875000.04569950.0335.20000015.466667
313748948.2595.05.0439.028.033.87-92.6666670.0179210.087.8000005.600000
415100876.00333.03.080.03.0292.00-8.6000000.13636422.026.6666671.000000
5152914623.3025.014.02102.0102.045.33-23.2000000.05444129.0150.1428577.285714
6146885630.877.021.03621.0327.017.22-18.3000000.073569399.0172.42857115.571429
7178095411.9116.012.02057.061.088.72-35.7000000.03910641.0171.4166675.083333
81531160767.900.091.038194.02379.025.54-4.1444440.315508474.0419.71428626.142857
9160982005.6387.07.0613.067.029.93-47.6666670.0243900.087.5714299.571429
customer_idgross_revenuerecency_daysqtd_invoicesqtd_itemsqtd_productsavg_ticketavg_recency_daysfrequencyqtd_returnsavg_basket_sizeavg_unique_basket_size
5627177271060.2515.01.0645.066.016.06-6.00.2857146.0645.00000066.0
563717232421.522.02.0203.036.011.71-12.00.1538460.0101.50000018.0
563817468137.0010.02.0116.05.027.40-4.00.4000000.058.0000002.5
564913596697.045.02.0406.0166.04.20-7.00.2500000.0203.00000083.0
5655148931237.859.02.0799.073.016.96-2.00.6666670.0399.50000036.5
565912479473.2011.01.0382.030.015.77-4.00.33333334.0382.00000030.0
568014126706.137.03.0508.015.047.08-3.01.00000050.0169.3333335.0
5686135211092.391.03.0733.0435.02.51-4.50.3000000.0244.333333145.0
569615060301.848.04.0262.0120.02.52-1.02.0000000.065.50000030.0
571512558269.967.01.0196.011.024.54-6.00.285714196.0196.00000011.0